• Korean Journal of Biological Psychiatry
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• v.25 no.1
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• pp.1-8
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• 2018

Insomnia is a common sleep-related symptom which occurs in many populations, however, the neural mechanism underlying insomnia is not yet known. The hyperarousal model explains the neural mechanism of insomnia to some extent, and the frontal cortex dysfunction has been known to be related to primary insomnia. In this review, we discuss studies that applied resting state and/or task-related functional magnetic resonance imaging to demonstrate the deficits/dysfunctions of functional activation and network in primary insomnia. Empirical evidence of the hyperarousal model and proposed relation between the frontal cortex and other brain regions in primary insomnia are examined. Reviewing these studies could provide critical insights regarding the pathophysiology, brain network and cerebral activation in insomnia and the development of novel methodologies for the diagnosis and treatment of insomnia.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.316-322
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• 2020

Endoscopic spine surgery is an advanced surgical technique for spinal surgery since it minimizes skin incision, muscle damage, and blood loss compared to open surgery. It requires, however, accurate positioning of an endoscope to avoid spinal nerves and to locate the endoscope near the target disk. Before the insertion of the endoscope, a guide needle is inserted to guide it. Also, the result of the surgery highly depends on the surgeons' experience and the patients' CT or MRI images. Thus, for the training, a number of haptic simulators for spinal needle insertion have been developed. But, still, it is difficult to be used in the medical field practically because previous studies require manual segmentation of vertebrae from CT images, and interaction force between the needle and soft tissue has not been considered carefully. This paper proposes AI-based automatic vertebrae CT-image segmentation and haptic rendering method using the proposed need-tissue interaction model. For the segmentation, U-net structure was implemented and the accuracy was 93% in pixel and 88% in IoU. The needle-tissue interaction model including puncture force and friction force was implemented for haptic rendering in the proposed spinal needle insertion simulator.

• The Academic Congress of Korean Shoulder and Elbow Society
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• 2009.03a
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• pp.74-74
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• 2009

The purpose of this study was to estimate force of muscles that constituted the rotator cuff during elevation motion in scapula plane, using a skeletal muscle model and quantitatively evaluate rotator cuff function in vivo. A healthy volunteer was measured with an open MR and CT system at elevation positions in scapula plane (MR: $30^{\circ}$, $60^{\circ}$, $90^{\circ}$, $120^{\circ}$, $150^{\circ}$, CT: $0^{\circ}$). After reconstruction three-dimensional MRI-based and CT-based bone surface models, matched each models with registration technique. Then supraspinatus, infraspinatus, subscapularis, teres minor, deltoid (anterior, middle, posterior portions) represented as plural lines. These lines were proportional to physiologic cross-sectional area (PCSA) and defined straight line to bind origin and insertion. Force of supraspinatus became greatest at $59^{\circ}$ of elevation. Subsequently force of deltoid middle portion became greatest at $89^{\circ}$ of elevation. Infraspinatus and subscapularis were active at the meantime. In addition, supraspinatus was active during elevation. These results resembled clinical finding and were proved force couples that contribute to mobility and stability of shoulder complex.

• Archives of Plastic Surgery
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• v.32 no.6
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• pp.796-797
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• 2005

In plastic and reconstructive craniomaxillofacial surgery, careful preoperative planning is essential to get a successful outcome. Many craniomaxillofacial surgeons have used imaging modalities like conventional radiographs, computed tomography(CT) and magnetic resonance imaging(MRI) for supporting the planning process. But, there are a lot of limitations in the comprehension of the surgical anatomy with these modalities. Medical models made with rapid prototyping (RP) technique represent a new approach for preoperative planning and simulation surgery. With rapid prototyping models, surgical procedures can be simulated and performed interactively so that surgeon can get a realistic impression of complex structures before surgical intervention. The great advantage of rapid prototyping technique is the precise reproduction of objects from a 3-dimensional reconstruction image as a physical model. Craniomaxillofacial surgeon can establish treatment strategy through preoperative simulation surgery and predict the postoperative result.

• Wind and Structures
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• v.31 no.2
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• pp.85-102
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• 2020

Accurate load evaluation is essential in any performance-based design. Design wind speeds and associated wind loads are well defined for synoptic boundary layer winds but not for thunderstorms. The method presented in the current study represents a new approach to obtain design wind speeds associated with thunderstorms and their gust fronts using historical data and Monte Carlo simulations. The method consists of the following steps (i) developing a numerical model for thunderstorm downdrafts (i.e. downbursts) to account for storm translation and outflow dissipation, (ii) utilizing the model to characterize previous events and (iii) extrapolating the limited wind speed data to cover life-span of structures. The numerical model relies on a previously generated CFD wind field, which is validated using six documented thunderstorm events. The model suggests that 10 parameters are required to describe the characteristics of an event. The model is then utilized to analyze wind records obtained at Lubbock Preston Smith International Airport (KLBB) meteorological station to identify the thunderstorm parameters for this location, obtain their probability distributions, and utilized in the Monte Carlo simulation of thunderstorm gust front events for many thousands of years for the purpose of estimating design wind speeds. The analysis suggests a potential underestimation of design wind speeds when neglecting thunderstorm gust fronts, which is common practice in analyzing historical wind records. When compared to the design wind speed for a 700-year MRI in ASCE 7-10 and ASCE 7-16, the estimated wind speeds from the simulation were 10% and 11.5% higher, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.7-12
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• 2012

Recently the medical field to efficiently process the vast amounts of information to decision trees, neural networks, Bayesian Networks, including the application method of various data mining techniques are investigated. In addition, the basic personal information or patient history, family history, in addition to information such as MRI, HRCT images and additional information to collect and leverage in the diagnosis of disease, improved diagnostic accuracy is to promote a common status. But in real world situations that affect the results much because of the variable exists for a particular data mining techniques to obtain information through the enemy can be seen fairly limited. Medical images were taken as well as a minor can not give a positive impact on the diagnosis, but the proportion increased subjective judgments by the automated system is to deal with difficult issues. As a result of a complex reality, the situation is more advantageous to deal with the relative probability of the multivariate model based on Bayesian network, or TAN in the K2 search algorithm improves due to expansion model has been proposed. At this point, depending on the type of search algorithm applied significantly influenced the performance characteristics of the extended Bayesian network, the performance and suitability of each technique for evaluation of the facts is required. In this paper, we extend the Bayesian network for diagnosis of diseases using the same data were carried out, K2, TAN and changes in search algorithms such as classification accuracy was measured. In the 10-fold cross-validation experiment was performed to compare the performance evaluation based on the analysis and the onset of high-risk classification for patients with HRCT images could be possible to identify high-risk data.

• Journal of the Korean Society of Radiology
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• v.85 no.2
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• pp.381-393
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• 2024

Purpose Metabolic abnormalities in hepatic encephalopathy (HE) cause brain edema or demyelinating disease, resulting in symmetric regional cerebral edema (SRCE) on MRI. This study aimed to investigate the usefulness of the clustering analysis of SRCE in predicting the development of brain failure. Materials and Methods MR findings and clinical data of 98 consecutive patients with HE were retrospectively analyzed. The correlation between the 12 regions of SRCE was calculated using the phi (φ) coefficient, and the pattern was classified using hierarchical clustering using the φ² distance measure and Ward's method. The classified patterns of SRCE were correlated with clinical parameters such as the model for end-stage liver disease (MELD) score and HE grade. Results Significant associations were found between 22 pairs of regions of interest, including the red nucleus and corpus callosum (φ = 0.81, p < 0.001), crus cerebri and red nucleus (φ = 0.72, p < 0.001), and red nucleus and dentate nucleus (φ = 0.66, p < 0.001). After hierarchical clustering, 24 cases were classified into Group I, 35 into Group II, and 39 into Group III. Group III had a higher MELD score (p = 0.04) and HE grade (p = 0.002) than Group I. Conclusion Our study demonstrates that the SRCE patterns can be useful in predicting hepatic preservation and the occurrence of cerebral failure in HE.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.193-221
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• 2017

Grouping episodes into semantically related categories is necessary for better mnemonic structure. However, the effect of grouping on memory of subordinate details was not clearly understood. In an fMRI study, we tested whether attending superordinate during semantic association disrupts or enhances subordinate episodic details. In each cycle of the experiment, five cue words were presented sequentially with two related detail words placed underneath for each cue. Participants were asked whether they could imagine a category that includes the previously shown cue words in each cycle, and their confidence on retrieval was rated. Participants were asked to perform cued recall tests on presented detail words after the session. Behavioral data showed that reaction times for categorization tasks decreased and confidence levels increased in the third trial of each cycle, thus this trial was considered to be an important insight where a semantic category was believed to be successfully established. Critically, the accuracy of recalling detail words presented immediately prior to third trials was lower than those of followed trials, indicating that subordinate details were disrupted during categorization. General linear model analysis of the trial immediately prior to the completion of categorization, specifically the second trial, revealed significant activation in the temporal gyrus and inferior frontal gyrus, areas of semantic memory networks. Representative Similarity Analysis revealed that the activation patterns of the third trials were more consistent than those of the second trials in the temporal gyrus, inferior frontal gyrus, and hippocampus. Our research demonstrates that semantic grouping can cause memories of subordinate details to fade, suggesting that semantic retrieval during categorization affects the quality of related episodic memory.

• Journal of Radiation Protection and Research
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• v.44 no.4
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• pp.149-155
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• 2019

Background: Magnetic resonance (MR) image guided radiation therapy system, enables real time MR guided radiotherapy (RT) without additional radiation exposure to patients during treatment. However, MR image lacks electron density information required for dose calculation. Image fusion algorithm with deformable registration between MR and computed tomography (CT) was developed to solve this issue. However, delivered dose may be different due to volumetric changes during image registration process. In this respect, synthetic CT generated from the MR image would provide more accurate information required for the real time RT. Materials and Methods: We analyzed 1,209 MR images from 16 patients who underwent MR guided RT. Structures were divided into five tissue types, air, lung, fat, soft tissue and bone, according to the Hounsfield unit of deformed CT. Using the deep learning model (U-NET model), synthetic CT images were generated from the MR images acquired during RT. This synthetic CT images were compared to deformed CT generated using the deformable registration. Pixel-to-pixel match was conducted to compare the synthetic and deformed CT images. Results and Discussion: In two test image sets, average pixel match rate per section was more than 70% (67.9 to 80.3% and 60.1 to 79%; synthetic CT pixel/deformed planning CT pixel) and the average pixel match rate in the entire patient image set was 69.8%. Conclusion: The synthetic CT generated from the MR images were comparable to deformed CT, suggesting possible use for real time RT. Deep learning model may further improve match rate of synthetic CT with larger MR imaging data.